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Dataset Title:  San Antonio Bay benthos species abundance before and after Hurricane Harvey,
Feb. 2017 - July 2019
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_784677)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   Maximum ?
 Sta (unitless) ?          "A"    "D"
 latitude (degrees_north) ?          28.24618    28.39352
  < slider >
 longitude (degrees_east) ?          -96.7724    -96.68435
  < slider >
 date_local (unitless) ?          "2017-02-22"    "2019-07-09"
 replicate (unitless) ?          1    3
 SpName (unitless) ?          "Acteocina canalicu..."    "Xenanthura brevite..."
 species_code (unitless) ?          2    655
 count (number/core) ?          1    152
 abundance (n/m²) ?          283.64    43113.28
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Sta {
    String bcodmo_name "station";
    String description "Station name";
    String long_name "Sta";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 28.24618, 28.39352;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Station latitude; north is positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -96.7724, -96.68435;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Station longitude; east is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  date_local {
    String bcodmo_name "date_local";
    String description "Date in Day-Month-Year format";
    String long_name "Date Local";
    String source_name "date_local";
    String time_precision "1970-01-01";
    String units "unitless";
  replicate {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String bcodmo_name "replicate";
    String description "Replicate number (1; 2; 3)";
    String long_name "Replicate";
    String units "unitless";
  SpName {
    String bcodmo_name "taxon";
    String description "Taxonomic name";
    String long_name "Sp Name";
    String units "unitless";
  species_code {
    Int16 _FillValue 32767;
    Int16 actual_range 2, 655;
    String bcodmo_name "taxon_code";
    String description "Species code";
    String long_name "Species Code";
    String units "unitless";
  count {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 152;
    String bcodmo_name "count";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Count: number/core where the core area is 35.4 cm^2";
    String long_name "Count";
    String units "number/core";
  abundance {
    Float32 _FillValue NaN;
    Float32 actual_range 283.64, 43113.28;
    String bcodmo_name "abundance";
    String description "Abundance";
    String long_name "Abundance";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "n/m²";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sediment samples were collected using cores deployed from small boats
(Montagna and Kalke 1992). Macrofauna were sampled with a 6.7-cm diameter core
tube (35.4 cm2 area).\\u00a0 The cores were sectioned at 0-3 cm and 3-10 cm
depths to ease the samples sorting and identification process for macrofauna
but summed for whole core analyses here.\\u00a0 Three replicates were taken per
station.\\u00a0 Organisms were extracted on a 0.5 mm sieve and enumerated to
the lowest taxonomic level possible.";
    String awards_0_award_nid "783255";
    String awards_0_award_number "OCE-1760006";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1760006";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
"Benthic macrofauna species abundance 
   San Antonio Bay, Feb-July, 2019 
   P.I.: P. Montagna (TAMUCC) 
   version date: 2019-12-18";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2019-12-18T21:11:08Z";
    String date_modified "2019-12-23T21:32:28Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.784677.1";
    Float64 Easternmost_Easting -96.68435;
    Float64 geospatial_lat_max 28.39352;
    Float64 geospatial_lat_min 28.24618;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -96.68435;
    Float64 geospatial_lon_min -96.7724;
    String geospatial_lon_units "degrees_east";
    String history 
"2022-10-01T15:27:54Z (local files)
2022-10-01T15:27:54Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_784677.html";
    String infoUrl "https://www.bco-dmo.org/dataset/784677";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_description "Used to identify macrofauna.";
    String instruments_0_dataset_instrument_nid "784757";
    String instruments_0_description "Instruments that generate enlarged images of samples using the phenomena of reflection and absorption of visible light. Includes conventional and inverted instruments. Also called a \"light microscope\".";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB05/";
    String instruments_0_instrument_name "Microscope-Optical";
    String instruments_0_instrument_nid "708";
    String instruments_0_supplied_name "Wild steromicroscope";
    String instruments_1_dataset_instrument_description "Used to collect sediment core samples.";
    String instruments_1_dataset_instrument_nid "784704";
    String instruments_1_description 
"Capable of being performed in numerous environments, push coring is just as it sounds. Push coring is simply pushing the core barrel (often an aluminum or polycarbonate tube) into the sediment by hand. A push core is useful in that it causes very little disturbance to the more delicate upper layers of a sub-aqueous sediment.

Description obtained from: http://web.whoi.edu/coastal-group/about/how-we-work/field-methods/coring/";
    String instruments_1_instrument_name "Push Corer";
    String instruments_1_instrument_nid "628287";
    String keywords "abundance, bco, bco-dmo, biological, chemical, code, count, data, dataset, date, dmo, erddap, latitude, local, longitude, management, name, oceanography, office, preliminary, replicate, species, species_code, SpName, sta, time";
    String license "https://www.bco-dmo.org/dataset/784677/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/784677";
    Float64 Northernmost_Northing 28.39352;
    String param_mapping "{'784677': {'Latitude': 'master - latitude', 'Longitude': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/784677/parameters";
    String people_0_affiliation "Texas A&M, Corpus Christi";
    String people_0_affiliation_acronym "TAMU-CC";
    String people_0_person_name "Paul A. Montagna";
    String people_0_person_nid "51205";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "Hurricane Harvey Texas Lagoons";
    String projects_0_acronym "Hurricane Harvey Texas Lagoons";
    String projects_0_description 
"NSF Award Abstract:
Hurricane Harvey made landfall Friday 25 August 2017 about 30 miles northeast of Corpus Christi, Texas as a Category 4 hurricane with winds up to 130 mph. This is the strongest hurricane to hit the middle Texas coast since Carla in 1961. After the wind storm and storm surge, coastal flooding occurred due to the storm lingering over Texas for four more days, dumping as much as 50 inches of rain near Houston. This will produce one of the largest floods ever to hit the Texas coast, and it is estimated that the flood will be a one in a thousand year event. The Texas coast is characterized by lagoons behind barrier islands, and their ecology and biogeochemistry are strongly influenced by coastal hydrology. Because this coastline is dominated by open water systems and productivity is driven by the amount of freshwater inflow, Hurricane Harvey represents a massive inflow event that will likely cause tremendous changes to the coastal environments. Therefore, questions arise regarding how biogeochemical cycles of carbon, nutrients, and oxygen will be altered, whether massive phytoplankton blooms will occur, whether estuarine species will die when these systems turn into lakes, and how long recovery will take? The investigators are uniquely situated to mount this study not only because of their location, just south of the path of the storm, but most importantly because the lead investigator has conducted sampling of these bays regularly for the past thirty years, providing a tremendous context in which to interpret the new data gathered. The knowledge gained from this study will provide a broader understanding of the effects of similar high intensity rainfall events, which are expected to increase in frequency and/or intensity in the future.
The primary research hypothesis is that: Increased inflows to estuaries will cause increased loads of inorganic and organic matter, which will in turn drive primary production and biological responses, and at the same time significantly enhance respiration of coastal blue carbon. A secondary hypothesis is that: The large change in salinity and dissolved oxygen deficits will kill or stress many estuarine and marine organisms. To test these hypotheses it is necessary to measure the temporal change in key indicators of biogeochemical processes, and biodiversity shifts. Thus, changes to the carbon, nitrogen and oxygen cycles, and the diversity of benthic organisms will be measured and compared to existing baselines. The PIs propose to sample the Lavaca-Colorado, Guadalupe, Nueces, and Laguna Madre estuaries as follows: 1) continuous sampling (via autonomous instruments) of salinity, temperature, pH, dissolved oxygen, and depth (i.e. tidal elevation); 2) bi-weekly to monthly sampling for dissolved and total organic carbon and organic nitrogen, carbonate system parameters, nutrients, and phytoplankton community composition; 3) quarterly measurements of sediment characteristics and benthic infauna. The project will support two graduate students. The PIs will communicate results to the public and to state agencies through existing collaborations.";
    String projects_0_end_date "2019-08";
    String projects_0_geolocation "Northwest Gulf of Mexico estuaries on Texas Coast";
    String projects_0_name "RAPID: Capturing the Signature of Hurricane Harvey on Texas Coastal Lagoons";
    String projects_0_project_nid "783256";
    String projects_0_start_date "2017-10";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 28.24618;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "The effects of Hurricane Harvey were studied. This dataset includes abundance of identified benthic macrofauna from sediment core samples collected in San Antonio Bay, northwest Gulf of Mexico estuaries along the Texas coast. They were collected during eleven quarterly sampling trips on a small boat, Feb. 2017 - July 2019";
    String title "San Antonio Bay benthos species abundance before and after Hurricane Harvey, Feb. 2017 - July 2019";
    String version "1";
    Float64 Westernmost_Easting -96.7724;
    String xml_source "osprey2erddap.update_xml() v1.3";


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tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
For example,
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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